correct

examples/BuddyLeNet/CMakeLists.txt

@@ -52,29 +52,6 @@ add_custom_command(
 
 set(ONE_SHOT_BUFFERIZE_OPTION "bufferize-function-boundaries=1 function-boundary-type-conversion=identity-layout-map")
 set(LOWER_TO_NVVM_OPTION "cubin-chip=sm_80 cubin-features=+ptx71 cubin-format=fatbin")
-# add_custom_command(
-#   OUTPUT subgraph0.o
-#   COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${BUDDY_EXAMPLES_DIR}/BuddyLeNet/subgraph0.mlir 
-#             -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" |
-#           ${LLVM_TOOLS_BINARY_DIR}/mlir-opt
-#           -one-shot-bufferize=${ONE_SHOT_BUFFERIZE_OPTION}
-#           -buffer-deallocation
-#           -convert-linalg-to-parallel-loops
-#           -canonicalize
-#           -gpu-map-parallel-loops
-#           -convert-parallel-loops-to-gpu
-#           -gpu-kernel-outlining
-#           -canonicalize
-#           -cse |
-#           ${BUDDY_BINARY_DIR}/buddy-opt -convert-memcpy-to-gpu -gpu-async-region -canonicalize |
-#           ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --test-lower-to-nvvm=${LOWER_TO_NVVM_OPTION} |
-#           ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir |
-#           ${LLVM_TOOLS_BINARY_DIR}/llvm-as |
-#           ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj  -relocation-model=pic -O0 -o ${BUDDY_BINARY_DIR}/../examples/BuddyLeNet/subgraph0.o
-#   DEPENDS ${BUDDY_EXAMPLES_DIR}/BuddyLeNet/subgraph0.mlir
-#   COMMENT "Building subgraph0.o"
-#   VERBATIM)
-
 add_custom_command(
   OUTPUT subgraph1.o
   COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${BUDDY_EXAMPLES_DIR}/BuddyLeNet/subgraph1.mlir 

frontend/Python/graph/json_decoder.py

@@ -1,3 +1,22 @@
+# ===- json_decoder.py ---------------------------------------------------------
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# ===---------------------------------------------------------------------------
+#
+# This converts the JSON string representing Buddy Graph into a Graph object.
+#
+# ===---------------------------------------------------------------------------
 import json
 from pathlib import Path
 
@@ -11,6 +30,7 @@
 from ..ops.math import ops_registry as math_ops_registry
 from ..ops.func import ops_registry as func_ops_registry
 
+
 def json_to_graph(json_str):
     """
     Converts a buddy graph JSON string to a Graph object.
@@ -21,6 +41,7 @@ def json_to_graph(json_str):
     Returns:
         Graph: The Graph object created from the JSON data.
     """
+
     def json_to_tensormeta(json_data):
         """
         Convert JSON data to a TensorMeta object.
@@ -31,68 +52,77 @@ def json_to_tensormeta(json_data):
         Returns:
             TensorMeta: The TensorMeta object created from the JSON data.
         """
-        if 'shape' in json_data:
-            shape = json_data['shape']
+        if "shape" in json_data:
+            shape = json_data["shape"]
             dtype = next(
-                (member for member in TensorDType.__members__.values() 
-                 if member.value.upper() == json_data['dtype'].upper()), None
+                (
+                    member
+                    for member in TensorDType.__members__.values()
+                    if member.value.upper() == json_data["dtype"].upper()
+                ),
+                None,
             )
             return TensorMeta(shape, dtype)
         return {}
-        
+
     json_data = json.loads(json_str)
     _graph = json_data
-    graph_name = _graph['graph_name'] 
+    graph_name = _graph["graph_name"]
     inputs = []
     params = []
-    for _input in _graph['inputs']:
+    for _input in _graph["inputs"]:
         inputs.append(json_to_tensormeta(_input))
-    for _param in _graph['params']:
+    for _param in _graph["params"]:
         params.append(json_to_tensormeta(_param))
     ops_registry = {}
     ops_registry.update(func_ops_registry)
     ops_registry.update(linalg_ops_registry)
     ops_registry.update(tosa_ops_registry)
     ops_registry.update(math_ops_registry)
-    graph = Graph(
-        inputs, 
-        params,
-        ops_registry, 
-        graph_name
-    )
-    graph.device = _graph['device']
-    for _node in _graph['nodes']:
-        op_class = _node['class']
+    graph = Graph(inputs, params, ops_registry, graph_name)
+    graph.device = _graph["device"]
+    for _node in _graph["nodes"]:
+        op_class = _node["class"]
         op = globals()[op_class]()
 
-        op._name = _node['name']
-        op._children = _node['children']
-        op._parents = _node['parents']
-        op._arguments = _node['arguments']
-        op._keyword_arguments = _node['keyword_arguments']
+        op._name = _node["name"]
+        op._children = _node["children"]
+        op._parents = _node["parents"]
+        op._arguments = _node["arguments"]
+        op._keyword_arguments = _node["keyword_arguments"]
         op._type = next(
-            (member for member in OpType.__members__.values() if member.value == _node['type']), None
+            (
+                member
+                for member in OpType.__members__.values()
+                if member.value == _node["type"]
+            ),
+            None,
         )
 
         # TODO : node attr tensor_meta should be  Class TensorMeta
-        if ('shape' not in _node['tensor_meta']):
-            op._tensor_meta = _node['tensor_meta']
+        if "shape" not in _node["tensor_meta"]:
+            op._tensor_meta = _node["tensor_meta"]
         else:
             op._tensor_meta = {
-                'shape' : _node['tensor_meta']['shape'],
-                'dtype' : next(
-                    (member for member in TensorDType.__members__.values() 
-                    if member.value.upper() == _node['tensor_meta']['dtype'].upper()), None
-                )
+                "shape": _node["tensor_meta"]["shape"],
+                "dtype": next(
+                    (
+                        member
+                        for member in TensorDType.__members__.values()
+                        if member.value.upper()
+                        == _node["tensor_meta"]["dtype"].upper()
+                    ),
+                    None,
+                ),
             }
         graph.add_node(op)
 
-    for i, device in enumerate(list(set(_graph['node_map_device'].values()))):
+    for i, device in enumerate(list(set(_graph["node_map_device"].values()))):
         subgraph_name = "subgraph{}".format(i)
         graph.op_groups[subgraph_name] = []
         graph.group_map_device[subgraph_name] = DeviceType(device)
 
-    for node, op_device in _graph['node_map_device'].items():
+    for node, op_device in _graph["node_map_device"].items():
         op = graph.node_table[node]
         for subgraph_name, group_device in graph.group_map_device.items():
             if op_device == group_device.value:

midend/lib/Conversion/MLIRGPU/ConvertMemcpyToGPU.cpp

@@ -211,4 +211,4 @@ void registerConvertMemcpyToGPUPass() {
   PassRegistration<ConvertMemcpyToGPUPass>();
 }
 } // namespace buddy
-} // namespace mlir
+} // namespace mlir

tests/Conversion/convert-memcpy-to-gpu.mlir

@@ -66,4 +66,4 @@ module attributes {gpu.container_module} {
       gpu.return
     }
   }
-}
+}